{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3d9aaf9a-1876-4008-b56a-367b84312f6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "from tsod import MVCorrelationDetector"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "040703b5",
   "metadata": {},
   "source": [
    "This notebook shows an example of using cross-correlation between time series to detect anomalies."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7aad1f35",
   "metadata": {},
   "source": [
    "# Generate normal and abnormal data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e23edb6",
   "metadata": {},
   "source": [
    "We generate data from three time series. The time series in rows 1 and 2 ($ts_1$ and $ts_2$) are defined as independent Gaussian observations with mean 2 and standard deviation 0.1. Hence these two time series are uncorrelated. We define the row 0 time series as a function of the two other time series: $ts_0 = 3ts_1 + ts_2$, making $ts_0$ correlated with both $ts_1$ and $ts_2$. \n",
    "\n",
    "For the abnormal data, the generation process is the same, except that we insert independent Gaussian data in a window in $ts_0$, making this part of $ts_0$ uncorrelated with the two other time series."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cda81c52",
   "metadata": {},
   "outputs": [],
   "source": [
    "n_obs = 100\n",
    "normal_data = pd.DataFrame(np.random.normal(size=[3, n_obs], loc=2.0, scale=0.1))\n",
    "normal_data.iloc[0, :] = 3*normal_data.iloc[1, :] + normal_data.iloc[2, :]\n",
    "abnormal_data = pd.DataFrame(np.random.normal(size=[3, n_obs], loc=2.0, scale=0.1))\n",
    "abnormal_data.iloc[0, :] = 3*abnormal_data.iloc[1, :] + abnormal_data.iloc[2, :]\n",
    "abnormal_data.iloc[0, 20:35] = np.random.normal(size=[1, 15], loc=2.0, scale=0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "354fcdc2",
   "metadata": {},
   "source": [
    "# Plot normal and abnormal data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "71ab34ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x18b7e51e8c8>,\n",
       " <matplotlib.lines.Line2D at 0x18b7e774888>,\n",
       " <matplotlib.lines.Line2D at 0x18b7e77d3c8>]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(normal_data.T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b11e8e5d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x18b7e8a2548>,\n",
       " <matplotlib.lines.Line2D at 0x18b7e8a24c8>,\n",
       " <matplotlib.lines.Line2D at 0x18b7e8b2248>]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(abnormal_data.T)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aaf2af8b",
   "metadata": {},
   "source": [
    "# Fit detector on normal data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c0075fa",
   "metadata": {},
   "source": [
    "We need normal data without anomalies to fit the detector so that the detector is able to learn the typical correlations to expect when data does not contain anomalies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "893fcde8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tsod.mvdetectors.MVCorrelationDetector at 0x18b7e8e5088>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "detector = MVCorrelationDetector(5)\n",
    "detector.fit(normal_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "712f13e5",
   "metadata": {},
   "source": [
    "# Run detector on abnormal data and visualize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a5b9a145",
   "metadata": {},
   "outputs": [],
   "source": [
    "detections = detector.detect(abnormal_data)\n",
    "any_ts_anomalous = np.any(detections, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9ebf9a00",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x18b7e430bc8>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(abnormal_data.T)\n",
    "plt.plot(any_ts_anomalous, label='Anomaly detected')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "333c5aeb",
   "metadata": {},
   "source": [
    "As seen in the above figure, there are some detections where the data is normal and not all time points in the anomalous window are detected. Since the windows used to calculate the cross-correlations are quite small, substantial uncertainty in the cross-correlation estimates is to be expected. Random fluctuation in estimates within this uncertainty cause some anomalous time points to be missed and some normal time points to be flagged. To obtain a better overview of where anomalies time periods arise, some post-processing that aggregates individual detections is necessary to decrease the effect of uncertainty in the cross-correlation estimates."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f20e2db8",
   "metadata": {},
   "source": [
    "## Post-process detections and visualize"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61a807f0",
   "metadata": {},
   "source": [
    "In this case, we a threshold on the proportion of detections in a window to decide whether the window is anomalous or not. These values will probably need to be tuned specifically for a new dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4504dc67",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x18b7e4eaa08>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(abnormal_data.T)\n",
    "plt.plot(any_ts_anomalous.rolling(10, center=True).mean() > 0.3, label='Anomalous window')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0085566d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "8a2fb420",
   "metadata": {},
   "source": [
    "# Run detector on normal data and visualize"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07d009d8",
   "metadata": {},
   "source": [
    "While we want to make sure we detect anomalies in the normal data, we also want to check that we do not make (too many) detections in normal data. This is what we inspect in the following."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "02e2c025",
   "metadata": {},
   "outputs": [],
   "source": [
    "detections = detector.detect(normal_data)\n",
    "any_ts_anomalous = np.any(detections, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d70ae998",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x18b7ea79a08>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(normal_data.T)\n",
    "plt.plot(any_ts_anomalous, label='Anomaly detected')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87b96f71",
   "metadata": {},
   "source": [
    "A few points in the normal data were detected as anomalous."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "573c371e",
   "metadata": {},
   "source": [
    "## Post-process detections and visualize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "76fddb31",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x18b7ea44e48>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(abnormal_data.T)\n",
    "plt.plot(any_ts_anomalous.rolling(10, center=True).mean() > 0.3, label='Anomalous window')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c3f0fac",
   "metadata": {},
   "source": [
    "After post-processing, we see that no anomalous windows were found."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
